Collusion resilient spread spectrum watermarking in M-band wavelets using GA-fuzzy hybridization

  • Authors:

  • Santi P. Maity;Seba Maity;Jaya Sil;Claude Delpha

  • Affiliations:

  • Department of Information Technology, Bengal Engineering & Science University, Shibpur, P.O. Botanic Garden, Howrah 711 103, India;Department of EI & ECE Engineering, College of Engineering & Management, Kolaghat, P.O. KTPP Township, Midnapur East 711 171, India;Department of Computer Science & Technology, Bengal Engineering & Science University, Shibpur, P.O. Botanic Garden, Howrah 711 103, India;Laboratoire des Signaux et Systemes, CNRS, Universite Paris-Sud XI (UPS), Suplec 3, rue Joliot-Curie 91192, France

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2013

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Abstract

This paper proposes a collusion resilient optimized spread spectrum (SS) image watermarking scheme using genetic algorithms (GA) and multiband (M-band) wavelets. M-band decomposition of the host image offers advantages of better scale-space tiling and good energy compactness. This bandpass-like decomposition makes watermarking robust against frequency selective fading-like gain (intelligent collusion) attack. On the other hand, GA would determine threshold value of the host coefficients (process gain i.e. the length of spreading code) selection for watermark casting along with the respective embedding strengths compatible to the gain of frequency response. First, a single bit watermark embedding algorithm is developed using independent and identically distributed (i.i.d) Gaussian watermark. This is further modified to design a high payload system for binary watermark image using a set of binary spreading code patterns. Watermark decoding performance is improved by multiple stage detection through cancelation of multiple bit interference (MBI) effect. Fuzzy logic is used to classify decision magnitudes in multiple group combined interference cancelation (MGCIC) used in the intermediate stage(s). Simulation results show convergence of GA and validate relative performance gain achieved in this algorithm compared to the existing works.